Remote Data Scientist Jobs in Canada
71 Data Scientist jobs in Canada available for remote work from home. Apply for positions such as Staff ML Data Scientist, Classic AI/ML Data Scientist, Senior Data Scientist - Ontology & Semantic Modeling and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design, train, and deploy LLM-based recommender systems while managing the full lifecycle from raw data to production. The role involves collaborating with science teams to implement large-scale distributed training and low-latency inference solutions.
The role involves framing business problems as machine learning tasks and developing predictive models using structured datasets. You will collaborate with data engineers to deploy these models into production while ensuring automated monitoring for data quality.
Design, develop, and maintain formal domain ontologies, taxonomies, and semantic schemas to support enterprise AI and analytics. Collaborate with engineering teams to ground LLM workflows and GraphRAG pipelines in trusted enterprise context.
The Data Scientist will own end-to-end analytics for growth marketing, partnering with cross-functional teams to optimize marketing channels and drive personalization. They will also design and interpret experiments to inform high-stakes investment decisions and build scalable analytical frameworks.
Design, develop, evaluate, and deploy recommendation, personalization, ranking, NLP, and GenAI models, including RAG-based features, while analyzing data and engineering features. Build evaluation frameworks, investigate model failures, collaborate with engineering and platform teams on production iteration, and communicate findings while maintaining documentation and compliant data practices.
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Lead the development and deployment of production-grade machine learning models for customer lifetime value, conversion propensity, lead quality, revenue optimization, and personalized product recommendations. Establish scalable ML practices using Databricks and MLflow, measure business impact through experiments, and provide technical leadership across Data Science and partner teams.
You will manage analytical relationships with partners to deliver actionable insights on supply health and pricing competitiveness. Additionally, you will design scalable, automated reporting workflows and leverage AI tools to streamline data analysis processes.
Own analytical relationships with a portfolio of travel technology partners, delivering and presenting recurring insights on supply health, pricing competitiveness, and performance. Build reusable reporting and automated workflows, conduct exploratory and statistical analyses, and translate findings into clear recommendations for partner, product, engineering, and business teams.
Build and own machine learning models that assess small-business financial health and support lending decisions, then deploy them with production monitoring, tests, and documentation. Partner with Credit and Product on underwriting policy, product terms, and where predictive modeling can improve lending decisions.
Lead cross-functional analytics projects to uncover insights and optimize the customer journey across the insurance business. Design experiments, maintain core metrics, and provide data-backed recommendations to influence product and revenue leadership.
You will analyze large datasets to differentiate between legitimate and fraud traffic while developing detection models to improve security product accuracy. Additionally, you will troubleshoot production issues and collaborate across teams to implement scalable security solutions.
Develop and adapt analytical methods to infer residence, displacement, and potentially poverty from mobile network operator data, and specify, test, and guide implementation with operator engineering teams. Support operator and internal stakeholder discussions, design analyses with privacy and operational constraints in mind, and improve reusable templates and training materials.
Develop, deploy, and optimize scalable machine learning and deep learning solutions for portfolio optimization, recommendations, personalization, forecasting, segmentation, and business insights. Architect cloud-based data workflows and pipelines, mentor data scientists, and collaborate with engineering, product, and business teams to deliver reliable solutions aligned with business goals.
Set cross-team data science priorities and lead the company KPI framework, including driver trees, sensitivity modeling, measurement standards, and reusable analytical automation. Establish governed self-service and agentic workflows, align Finance and Product on targets and trade-offs, and mentor scientists while driving adoption of trusted metrics.
You will lead a team of data scientists to architect and build predictive models, measurement frameworks, and data products for advertising. You will also partner with product and engineering teams to scale these systems from prototype to production while championing methodology to stakeholders.
You will design and interpret product experiments while developing predictive models to optimize user engagement and retention. You will also partner with cross-functional teams to define KPI frameworks and translate analytical findings into actionable product strategies.
You will own company-wide KPI frameworks and measurement workstreams to drive business outcomes and product strategy. This involves building reproducible analytical tools, modeling KPI drivers, and partnering cross-functionally to ensure data-driven decision-making.
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You will serve as the senior analytical leader for the Play business, shaping strategy through advanced modeling, experimentation, and cross-functional collaboration. You will mentor team members and translate complex data into actionable recommendations for executive leadership.
Design, develop, and optimize advanced Pricing and Revenue Growth Management models to support strategic commercial decisions. Collaborate with cross-functional teams to translate complex business challenges into statistically robust predictive models.
You will own the scientific and product roadmap for the Monetization domain, leading the development of audience creation and measurement products. This involves collaborating with cross-functional teams to turn data signals into actionable insights and scalable commercial products.
You will independently own a defined audience or measurement product, managing the full lifecycle from problem framing to delivery. You will partner with cross-functional teams to translate advertiser goals into predictive models and actionable datasets.
The Staff Data Scientist will define and own the company-wide measurement framework, causal strategy, and semantic data architecture. They will lead scientific governance, oversee strategic modeling, and raise the technical maturity of the organization through mentorship and best practices.
You will own the data science strategy and roadmap for ranking and relevance, partnering with engineering and product teams to optimize marketplace outcomes. This involves designing experiments, building measurement frameworks, and translating complex business goals into actionable ranking improvements.
Design and deploy real-time courier pay and boost algorithms to balance supply with delivery demand. Lead causal inference and experimentation frameworks to measure incremental impact while collaborating with product and engineering teams.
Design and deploy real-time courier pay and boost algorithms to balance supply with delivery demand. Lead causal inference and experimentation frameworks to measure incremental impact while collaborating with product and engineering teams.
The Associate Data Scientist will assist with client engagements by measuring data de-identification and re-identification risks. Responsibilities include preparing client datasets, validating data, and supporting the delivery of privacy solutions through reports and remote coaching.
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The role involves designing, implementing, and validating algorithmic components within a consulting project team. You will also develop services and APIs to integrate applications with algorithms while solving mathematical optimization and operations research problems.
The Data Scientist will collect, clean, and analyze structured and unstructured data to solve business problems. They will also assist in building machine learning models and creating data visualizations to support product development.
The Senior Data Scientist will own a portfolio of customer deployments, proactively identifying performance issues and diagnosing system failures. They will also encode operational expertise into AI logic, validate model performance, and collaborate with cross-functional teams to drive impact.
You will partner with cross-functional leaders to shape the growth strategy, size opportunities, and prioritize the product roadmap. Additionally, you will own the growth funnel metrics and design experiments to drive customer acquisition, activation, and retention.
Stop the endless job search. Our AI finds and applies to the best jobs for you.
We reviewed 21 job postings for remote Data Scientists in Canada and found these are the skills employers ask for most often:
| Skill | Share of job posts |
|---|---|
| SQL | 95% |
| Python | 86% |
| Machine Learning | 81% |
| Causal Inference | 57% |
| Data Science | 52% |
| Statistical Modeling | 38% |
| Data Analysis | 29% |
| R | 24% |
| Communication | 24% |
| Predictive Modeling | 24% |
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